{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--BOOK_INFORMATION-->\n",
    "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PDSH-cover-small.png\">\n",
    "\n",
    "*This notebook contains an excerpt from the [Python Data Science Handbook](http://shop.oreilly.com/product/0636920034919.do) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/PythonDataScienceHandbook).*\n",
    "\n",
    "*The text is released under the [CC-BY-NC-ND license](https://creativecommons.org/licenses/by-nc-nd/3.0/us/legalcode), and code is released under the [MIT license](https://opensource.org/licenses/MIT). If you find this content useful, please consider supporting the work by [buying the book](http://shop.oreilly.com/product/0636920034919.do)!*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Simple Line Plots](04.01-Simple-Line-Plots.ipynb) | [Contents](Index.ipynb) | [Visualizing Errors](04.03-Errorbars.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Scatter Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another commonly used plot type is the simple scatter plot, a close cousin of the line plot.\n",
    "Instead of points being joined by line segments, here the points are represented individually with a dot, circle, or other shape.\n",
    "We’ll start by setting up the notebook for plotting and importing the functions we will use:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('seaborn-whitegrid')\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scatter Plots with ``plt.plot``\n",
    "\n",
    "In the previous section we looked at ``plt.plot``/``ax.plot`` to produce line plots.\n",
    "It turns out that this same function can produce scatter plots as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 30)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y, 'o', color='black');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The third argument in the function call is a character that represents the type of symbol used for the plotting. Just as you can specify options such as ``'-'``, ``'--'`` to control the line style, the marker style has its own set of short string codes. The full list of available symbols can be seen in the documentation of ``plt.plot``, or in Matplotlib's online documentation. Most of the possibilities are fairly intuitive, and we'll show a number of the more common ones here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = np.random.RandomState(0)\n",
    "for marker in ['o', '.', ',', 'x', '+', 'v', '^', '<', '>', 's', 'd']:\n",
    "    plt.plot(rng.rand(5), rng.rand(5), marker,\n",
    "             label=\"marker='{0}'\".format(marker))\n",
    "plt.legend(numpoints=1)\n",
    "plt.xlim(0, 1.8);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.5488135 , 0.71518937, 0.60276338, 0.54488318, 0.4236548 ])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = np.random.RandomState(0)\n",
    "rng.rand(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For even more possibilities, these character codes can be used together with line and color codes to plot points along with a line connecting them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, '-ok');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Additional keyword arguments to ``plt.plot`` specify a wide range of properties of the lines and markers:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y, '-p', color='gray',\n",
    "         markersize=15, linewidth=4,\n",
    "         markerfacecolor='white',\n",
    "         markeredgecolor='gray',\n",
    "         markeredgewidth=2)\n",
    "plt.ylim(-1.2, 1.2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This type of flexibility in the ``plt.plot`` function allows for a wide variety of possible visualization options.\n",
    "For a full description of the options available, refer to the ``plt.plot`` documentation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scatter Plots with ``plt.scatter``\n",
    "\n",
    "A second, more powerful method of creating scatter plots is the ``plt.scatter`` function, which can be used very similarly to the ``plt.plot`` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y, marker='o');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The primary difference of ``plt.scatter`` from ``plt.plot`` is that it can be used to create scatter plots where the properties of each individual point (size, face color, edge color, etc.) can be individually controlled or mapped to data.\n",
    "\n",
    "Let's show this by creating a random scatter plot with points of many colors and sizes.\n",
    "In order to better see the overlapping results, we'll also use the ``alpha`` keyword to adjust the transparency level:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = np.random.RandomState(0)\n",
    "x = rng.randn(100)\n",
    "y = rng.randn(100)\n",
    "colors = rng.rand(100)\n",
    "sizes = 1000 * rng.rand(100)\n",
    "\n",
    "plt.scatter(x, y, c=colors, s=sizes, alpha=0.3,\n",
    "            cmap='viridis')\n",
    "plt.colorbar();  # show color scale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the color argument is automatically mapped to a color scale (shown here by the ``colorbar()`` command), and that the size argument is given in pixels.\n",
    "In this way, the color and size of points can be used to convey information in the visualization, in order to visualize multidimensional data.\n",
    "\n",
    "For example, we might use the Iris data from Scikit-Learn, where each sample is one of three types of flowers that has had the size of its petals and sepals carefully measured:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "iris = load_iris()\n",
    "features = iris.data.T\n",
    "\n",
    "plt.scatter(features[0], features[1], alpha=0.2,\n",
    "            s=100*features[3], c=iris.target, cmap='viridis')\n",
    "plt.xlabel(iris.feature_names[0])\n",
    "plt.ylabel(iris.feature_names[1]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "iris = load_iris()\n",
    "features = iris.data.T\n",
    "\n",
    "plt.scatter(features[0], features[1], alpha=0.2,\n",
    "            s=100*features[3], c=iris.target)\n",
    "plt.xlabel(iris.feature_names[0])\n",
    "plt.ylabel(iris.feature_names[1]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that this scatter plot has given us the ability to simultaneously explore four different dimensions of the data:\n",
    "the (x, y) location of each point corresponds to the sepal length and width, the size of the point is related to the petal width, and the color is related to the particular species of flower.\n",
    "Multicolor and multifeature scatter plots like this can be useful for both exploration and presentation of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ``plot`` Versus ``scatter``: A Note on Efficiency\n",
    "\n",
    "Aside from the different features available in ``plt.plot`` and ``plt.scatter``, why might you choose to use one over the other? While it doesn't matter as much for small amounts of data, as datasets get larger than a few thousand points, ``plt.plot`` can be noticeably more efficient than ``plt.scatter``.\n",
    "The reason is that ``plt.scatter`` has the capability to render a different size and/or color for each point, so the renderer must do the extra work of constructing each point individually.\n",
    "In ``plt.plot``, on the other hand, the points are always essentially clones of each other, so the work of determining the appearance of the points is done only once for the entire set of data.\n",
    "For large datasets, the difference between these two can lead to vastly different performance, and for this reason, ``plt.plot`` should be preferred over ``plt.scatter`` for large datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Simple Line Plots](04.01-Simple-Line-Plots.ipynb) | [Contents](Index.ipynb) | [Visualizing Errors](04.03-Errorbars.ipynb) >\n",
    "\n",
    "<a href=\"https://colab.research.google.com/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open and Execute in Google Colaboratory\"></a>\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
